Recent advances in sensor technology for a broad class of applications have resulted in the evolution of sophisticated hardware for high resolution multispectral imaging. Multispectral imaging and associated cutting edge multispectral image and data fusion processing software have led to the realization of techniques which add significantly to the ability of identifying and characterizing the nature of scenes on the earth from space, or the identification of other objects from their multispectral and spatial signatures. A multispectral image fusion system is proposed which will present additional diagnostic information to a clinical or research ophthalmologist. Using state-of-the-art multispectral image capture system, advanced multispectral image fusion techniques inspired by the human vision system, and neural network feature classification algorithms, a Multispectral Image fusion System for detection and identification of ocular pathological features is described.